Random access communications in a wireless communication system

Abstract

A method, system and apparatus are disclosed. According to some embodiments, a method implemented by a UE is provided. The method includes receiving an indication of a first set of beams associated with a plurality of Synchronization Signal Blocks, SSBs, receiving an indication of a second set of beams associated with a plurality of random access channel, RACH, occasions where the first set of beams corresponds to a number of beams that is less than a number of beams of the second set of beams. The method further includes performing at least one measurement of at least one beam of the first set of beams, and transmitting physical random access channel, PRACH, signaling on a beam of the second set of beams based on the at least one measurement.

Description

[0001] RANDOM ACCESS COMMUNICATIONS IN A WIRELESS COMMUNICATION SYSTEM

[0002] TECHNICAL FIELD

[0003] The present disclosure relates to wireless communications, and in particular, to random access channel (RACH) communications for initial access.

[0004] BACKGROUND

[0005] The Third Generation Partnership Project (3GPP) has developed and is developing standards for Fourth Generation (4G) (also referred to as Long Term Evolution (LTE)) and Fifth Generation (5G) (also referred to as New Radio (NR)) wireless communication systems. Such systems provide, among other features, broadband communication between network nodes, such as base stations, and mobile user equipment (UE), as well as communication between network nodes and between UEs. The 3GPP is also developing standards for Sixth Generation (6G) wireless communication networks.

[0006] AI / ML in cellular networks

[0007] Artificial intelligence (Al) and machine learning (ML) have been investigated as possible tools to optimize the design of the air-interface in wireless communication networks in both academia and industry. Example use cases include using autoencoders for channel state information (CSI) compression to reduce the feedback overhead and improve channel prediction accuracy, using deep neural networks for classifying line-of- sight (LOS) and non-line-of-sight (NLOS) conditions to enhance the positioning accuracy, and using reinforcement learning for beam selection at the network side and / or the UE side to reduce the signaling overhead and beam alignment latency, using deep reinforcement learning to learn an optimal precoding policy for complex multiple-input multiple-output (MIMO) precoding problems.

[0008] In 3GPP NR standardization work, there is a Release 18 study item (SI) on AI / ML for NR air interface. This study item will explore the benefits of augmenting the airinterface with features enabling improved support of AI / ML based algorithms for enhanced performance and / or reduced complexity / overhead. Through studying a few selected use cases (CSI feedback, beam management and positioning), this SI aims to lay the foundation for future air-interface use cases leveraging AI / ML techniques.

[0009] AI / ML beam management (BM) enhancements One idea behind the AI / ML beam management (BM) enhancements considered in 3GPP Rel-18 is to reduce the number of measurements required in order to determine the beam used by the network for data transmission / reception. With this objective, the BM use case consider one-sided AI / ML models, located in either the network node or the UE, to predict one or more “good” beams for data transmission / reception from sparse measurements. It has been proposed that the best downlink beam predictions within a Set A of beams (e.g., the best CSI-RS beam that is subsequently used for downlink / uplink transmissions) should be performed based on measurement results of a sparser Set B of downlink beams (e.g., the SSB beams used for initial access). This concept is illustrated in FIG. 1 which is a diagram of a visual illustration of the definition of Set A and Set B within the AI / ML BM use case where Set A contains all 32 CSLRS beams and several examples of Set Bs are illustrated (4 SSB beams, 8 SSB beams, 4 CSLRS beams, 8 CSI- RS beams, and 16 CSI-RS beams). The circles in FIG. 1 indicate a “pointing angle” of each CSI-RS beam from the antenna array.

[0010] FIG. 2 is a diagram of the performance of the AI / ML schemes when considering different Set B alternatives against:

[0011] 1. A baseline solution consisting in selecting the best beam from the Set B of beams. All beams in Set B are sounded by the network node and measurements are reported by the UE. The reference signal overhead of the baseline solution is equal to the number of beams in the Set B; and

[0012] 2. A conventional hierarchical scheme divided into two stages: A first stage where the network node sounds all wide SSB beams and the UE informs the network of the strongest SSB beam, and a second stage where the network sounds the K narrow CSI-RS beams closest to the strongest SSB beam. Here, beam in terms of beam angle difference is defined as squared zenith angle difference plus squared azimuth angle difference. The reference signal overhead of the conventional scheme is, therefore, equal to the number of SSB beams + the number K of narrow CSI-RS beams within each SSB beam (K=4 in the results of FIG. 2).

[0013] Initial access in 5G NR

[0014] The UE may be required to initially connect to and be identified by the network node when it wants to establish communication with the network. With this purpose, the network node broadcasts SS blocks containing synchronization sequences and the physical broadcast channel (PBCH), which are typically sequentially beamformed in different spatial directions in FR2 as illustrated in FIG. 3. The latter includes the master information block (MIB), which in turn is used to acquire the remaining system information (SIB1) that a UE needs to know before attempting random access. Subsequently, two distinct Random Access Channel (RACH) procedures are defined in 5G NR.

[0015] 4-step RACH

[0016] FIG. 4 is a diagram of an example of 4-step RACH according to 3GPP Rel-15 procedure and it consists of the following steps:

[0017] • Step 0: the network operating at high frequencies transmits the beamformed synchronization signal block (SSB) in different spatial directions. An example of beamformed SSBs is illustrated in FIG. 3.

[0018] • Step 1 : The UE transmits the Physical Random-Access Channel (PRACH) preamble. The UE transmission will be performed in a RACH occasion associated with an SSB beamforming direction where a high RSRP has been measured as illustrated in FIG.

[0019] 5. Existing 3GPP specification allows to associate several RACH occasions to a given SSB time indices as illustrated in FIG. 5. That is, for example, beam #1 is used by the network node to transmit SSB#1 and to listen for / receive RACH occasion #1 and RACH occasion #2.

[0020] • Step 2: The network transmits a Random -Access Response (RAR) indicating that the PRACH preamble has been received and the timing advance to be used by UE for subsequent transmissions.

[0021] • Step 3: Using uplink shared channel (UL-SCH) resources, the UE transmits the Message 3 including a device identity.

[0022] • Step 4: The network node transmits Message 4 to resolve potential collisions in Step 1, which may occur when multiple devices simultaneously utilize an identical PRACH preamble, and to the connected state.

[0023] 2 -step RACH

[0024] This procedure was introduced in 3 GPP Rel-16 with the objectives of reducing the transmission delay for latency sensitive traffic and the UE power consumption for the transmission of small packets. The 2-step RACH process is illustrated in FIG. 6 and it is comprised of the following steps:

[0025] • Step 1 : The UE transmits Message A, which is a combination of the PRACH preamble (Step 1 in the 4-step RACH) and Message 3 (Step 3 in the 4-step RACH). This entails that the UE identification and uplink data transmissions may be immediately performed within PUSCH after the PRACH preamble transmission. For instance, the device may also include buffer status reports (BSRs) in Message 3. Illustrative short and long lengths of such PUSCH transmissions are 72 bits and 1000 bits, respectively.

[0026] • Step 2: The network transmits Message B, which is a combination of the RAR response (Step 2 in the 4-step RACH) and Message 4 (Step 4 in the 4-step RACH).

[0027] In 5GNR, the UE assumes a 1-to-l mapping between the spatial beams used to perform the downlink SSB transmissions and subsequently receive the uplink RACH transmissions. In these setups, the network dimensions the number of SSB beams to cover all spatial directions while providing sufficient beamforming gain for the subsequent uplink transmissions. Since there exists a substantial power imbalance between uplink and downlink (i.e., in the order of 20 dB), this requires that the network node must utilize a large number of narrow beams — up to 64 beams — for performing SSB transmissions in coverage-limited setups.

[0028] SUMMARY

[0029] Some embodiments advantageously provide methods, systems, and apparatuses for random access channel (RACH) communications. One or more embodiments related to one or more methods are described as follows:

[0030] • Step 1 : In some embodiments, the network node may indicate the following information to be received by the UE prior to performing initial access. Such indication may be performed, e.g., i) within the SIB1 of 5G NR or signaling with similar functionality in other 3GPP specifications, and / or ii) in SIB(s) different from SIB1 or signaling with similar functionality in other specifications for RRC CONNECTED UEs, and / or iii) in a UE-specific manner via, e.g., an RRC message, a MAC control element (CE), or a LI message. In such embodiments, at least one of the information fields may be included: o RRC state of the UE: Indicating the RRC states (e.g., RRC CONNECTED, RRC INACTIVE, RRC IDLE) for which the other information fields are applicable. o Indication of whether the network node receives RACH transmissions utilizing a larger number of spatial beams than the number of spatial beams used for performing SSB transmissions (i.e., the method described herein is executed):

[0031] ■ In some embodiments, the network node will perform such an indication via a Boolean information field.

[0032] ■ In some embodiments, the network node will indicate the unique ID associated with each RACH occasion. In the method described herein, the ID will correspond to a specific beam utilized for receiving RACH transmissions.

[0033] • The number of unique IDs may be larger than the number / quantity of SSB beams if a larger number / quantity of beams are used for RACH reception. o Allocation of the RACH resources with beams different from those used for SSB transmission: Time and frequency of the RACH occasions the PRACH preamble detection will be performed utilizing beams different from those used for SSB transmission. o UE model assistance information: Information that the UE can subsequently utilize in Step 1 to identify the model that should be executed to determine the RACH occasion where initial access should be attempted or as an input of a model with the same objective. o Indication for UEs without RACH model capability: Indication of the procedure that should be followed by UEs to determine the RACH occasion to perform initial access when UEs are not capable of executing a model that determines the RACH occasion for initial access when there exist RACH occasions associated with narrow beams. o UE model transfer: The network node may transfer model(s) (e.g., Al and / or ML models, non- Al and / or ML models) to be subsequently executed by the UE attempting to perform initial access in systems implementing the method described herein.

[0034] In other embodiments, the mandatory or optional inclusion of one or more of the above information fields as well as the values of such information fields may be indicated by the standard specification (e.g., 3GPP specification) and, consequently, the network information broadcast of such fields may not be performed.

[0035] In some embodiments, several replicas of the above information fields, each applicable only to certain UEs RRC states and with potentially different values, may be included.

[0036] In some embodiments, the network node determines whether to include some of the above information fields and / or the values of such information fields based on the UE capability indication provided in the optional Step 5.

[0037] • Step 2: Based on the information received in Step 1, the UE decides at least the at least one RACH occasion used for the transmission of at least the PRACH preamble. o In embodiments where the UE determines that the method described herein is being executed by the network node, the UE will execute a model whose output will determine one or more RACH occasions where the initial access attempt should be performed.

[0038] • Step 3 : The UE performs the initial access attempt in the at least one RACH occasion with the configuration determined in Step 2.

[0039] • [Optional Step]: The network node requests the UE to indicate whether the UE has the capability to execute one or more of the network indications described in Step 1. o In some embodiments, the network node may perform such a request via a network node-sent UE CapabilityEnquiry message, e.g., UECapabilityEnquiry message.

[0040] • [Optional Step]: The UE indicates to the network node whether it has the capability to execute one or more of the network indications described in Step 1 and / or whether additional information is required to be provided by the network node to execute such indications. o In some embodiments, the UE may communicate to the network node such capability via a UECapability Information message.

[0041] According to one aspect of the present disclosure, a method implemented by a user equipment, UE, that is configured to communicate with a network node is provided. An indication of a first set of beams associated with a plurality of Synchronization Signal Blocks, SSBs is received. An indication of a second set of beams associated with a plurality of random access channel, RACH, occasions, is received where the first set of beams corresponds to a number of beams that is less than a number of beams of the second set of beams. At least one measurement of at least one beam of the first set of beams is performed. Physical random access channel, PRACH, signaling is transmitted on a beam of the second set of beams based on the at least one measurement.

[0042] According to one or more embodiments of this aspect, the at least one beam of the second set of beams for transmission of the PRACH signaling is selected, using a machine learning model, based on the at least one measurement.

[0043] According to one or more embodiments of this aspect, further comprising receiving an indication of the machine learning model is received, and the machine learning model is implemented based on the received indication.

[0044] According to one or more embodiments of this aspect, at least one of the first set of beams has at least one predefined relationship with respect to at least one of the second set of beams. According to one or more embodiments of this aspect, the at least one predefined relationship is at least one spatial relationship.

[0045] According to one or more embodiments of this aspect, an indication is received of at least one radio resource control, RRC, state during which a configuration of the second set of beams associated with a plurality of RACH occasions can be used by the UE.

[0046] According to one or more embodiments of this aspect, an indication is received that at least one of the the second set of beams associated with a plurality of RACH occasions is spatially contained within one of the first set of beams associated with a plurality of SSBs.

[0047] According to one or more embodiments of this aspect, the second set of beams associated with a plurality of RACH occasions corresponds to a plurality of beams configured for channel state information-reference signal, CSI-RS, transmission.

[0048] According to one or more embodiments of this aspect, UE capability information is transmitted where the indication of the first set of beams and the second set of beams being in response to the UE capability information.

[0049] According to one or more embodiments of this aspect, the indication of the first set of beams and the indication of the second set of beams are included in one of: at least one system information block, SIB; radio resource control, RRC, signaling; or layer 1, LI, message.

[0050] According to one or more embodiments of this aspect, the PRACH signaling comprises a PRACH preamble of a random access procedure.

[0051] According to one or more embodiments of this aspect, an indication is received that indicates a UE transmission power for transmitting the PRACH signaling is based on at least one characteristic of the second set of beams.

[0052] According to one or more embodiments of this aspect, an indication is received in the first set of beams, where the indication indicates at least one procedure to implement at the UE if the UE lacks a capability to use a machine learning model for beam selection.

[0053] According to another aspect of the present disclosure, a user equipment, UE, configured to communicate with a network node is provided. The UE is configured to: receive an indication of a first set of beams associated with a plurality of Synchronization Signal Blocks, SSBs, receive an indication of a second set of beams associated with a plurality of random access channel, RACH, occasions, the first set of beams corresponding to a number of beams that is less than a number of beams of the second set of beams, perform at least one measurement of at least one beam of the first set of beams, and transmit physical random access channel, PRACH, signaling on a beam of the second set of beams based on the at least one measurement.

[0054] According to one or more embodiments of this aspect, the UE is further configured to select, using a machine learning model, the at least one beam of the second set of beams for transmission of the PRACH signaling based on the at least one measurement.

[0055] According to one or more embodiments of this aspect, the UE is further configured to receive an indication of the machine learning model, and implement the machine learning model based on the received indication.

[0056] According to one or more embodiments of this aspect, at least one of the first set of beams has at least one predefined relationship with respect to at least one of the second set of beams.

[0057] According to one or more embodiments of this aspect, the at least one predefined relationship is at least one spatial relationship.

[0058] According to one or more embodiments of this aspect, the UE is further configured to receive an indication of at least one radio resource control, RRC, state during which a configuration of the second set of beams associated with a plurality of RACH occasions can be used by the UE.

[0059] According to one or more embodiments of this aspect, the UE is further configured to receive an indication that at least one of the second set of beams associated with a plurality of RACH occasions is spatially contained within one of the first set of beams associated with a plurality of SSBs.

[0060] According to one or more embodiments of this aspect, the second set of beams associated with a plurality of RACH occasions corresponds to a plurality of beams configured for channel state information-reference signal, CSI-RS, transmission.

[0061] According to one or more embodiments of this aspect, the UE is further configured to transmit UE capability information, the indication of the first set of beams and the second set of beams being in response to the UE capability information.

[0062] According to one or more embodiments of this aspect, the indication of the first set of beams and the indication of the second set of beams are included in one of: at least one system information block, SIB, radio resource control, RRC, signaling, or layer 1, LI, message.

[0063] According to one or more embodiments of this aspect, the PRACH signaling comprises a PRACH preamble of a random access procedure. According to one or more embodiments of this aspect, the UE is further configured to receive an indication that indicates a UE transmission power for transmitting the PRACH signaling is based on at least one characteristic of the second set of beams.

[0064] According to one or more embodiments of this aspect, the UE is further configured to receive an indication in the first set of beams, where the indication indicates at least one procedure to implement at the UE if the UE lacks a capability to use a machine learning model for beam selection.

[0065] According to another aspect of the present disclosure, a method implemented by a network node that is configured to communicate with a user equipment, UE is provided. A first set of beams associated with a plurality of Synchronization Signal Blocks, SSBs is indicated. A second set of beams associated with a plurality of random access channel, RACH, occasions is indicated where the first set of beams corresponds to a number of beams that is less than a number of beams of the second set of beams. Physical random access channel, PRACH, signaling is received on a beam of the second set of beams, where the PRACH signaling is received based on measurement performed on at least one of the first set of beams.

[0066] According to one or more embodiments of this aspect, the first set of beams associated with a plurality of SSBs and the second set of beams associated with a plurality of RACH occasions are determined for initial access.

[0067] According to one or more embodiments of this aspect, at least one of the beams of the second set of beams associated with a plurality of RACH occasions are configured for selection by the UE using a machine learning model.

[0068] According to one or more embodiments of this aspect, an indication of a machine learning model to use for beam selection is transmitted to the UE.

[0069] According to one or more embodiments of this aspect, at least one of the first set of beams has at least one predefined relationship with respect to at least one of the second set of beams.

[0070] According to one or more embodiments of this aspect, the at least one predefined relationship is a spatial relationship.

[0071] According to one or more embodiments of this aspect, an indication is transmitted of at least one radio resource control, RRC, state during which a configuration of the second set of beams associated with the plurality of RACH occasions can be used by the UE. According to one or more embodiments of this aspect, an indication that at least one of the second set of beams associated with a plurality of RACH occasions is spatially contained within one of the first set of beams associated with a plurality of SSBs is transmitted.

[0072] According to one or more embodiments of this aspect, the second set of beams associated with a plurality of RACH occasions are configured to correspond to a plurality of beams configured for channel state information-reference signal, CSI-RS, transmission.

[0073] According to one or more embodiments of this aspect, UE capability information is received from the UE, where the indication of the first set of beams and the indication of the second set of beams is in response to the UE capability information.

[0074] According to one or more embodiments of this aspect, the indication of the first set of beams and the indication of the second set of beams are included in one of: at least one system information block, SIB; radio resource control, RRC, signaling; or layer 1, LI, message.

[0075] According to one or more embodiments of this aspect, the PRACH signaling comprises a PRACH preamble of a random access procedure.

[0076] According to one or more embodiments of this aspect, an indication is transmitted where the indication indicates a UE transmission power for transmitting the PRACH signaling is based on at least one characteristic of the second set of beams.

[0077] According to one or more embodiments of this aspect, an indication is transmitted in the first set of beams, where the indication indicates at least one procedure to implement at the UE if the UE lacks the capability to use a machine learning model for beam selection.

[0078] According to another aspect of the present disclosure, a network node that is configured to communicate with a user equipment, UE is provided. The network node is configured to: indicate a first set of beams associated with a plurality of Synchronization Signal Blocks, SSBs, indicate a second set of beams associated with a plurality of random access channel, RACH, occasions, where the first set of beams corresponds to a number of beams that is less than a number of beams of the second set of beams, and receive physical random access channel, PRACH, signaling on a beam of the second set of beams, the PRACH signaling being received based on measurement performed on at least one of the first set of beams.

[0079] According to one or more embodiments of this aspect, the network node is further configured to determine, for initial access, where the first set of beams associated with a plurality of SSBs and the second set of beams is associated with a plurality of RACH occasions.

[0080] According to one or more embodiments of this aspect, at least one of the beams of the second set of beams associated with a plurality of RACH occasions are configured for selection by the UE using a machine learning model.

[0081] According to one or more embodiments of this aspect, the network node is further configured to transmit, to the UE, an indication of a machine learning model to use for beam selection.

[0082] According to one or more embodiments of this aspect, at least one of the first set of beams has at least one predefined relationship with respect to at least one of the second set of beams.

[0083] According to one or more embodiments of this aspect, the at least one predefined relationship is a spatial relationship.

[0084] According to one or more embodiments of this aspect, the network node is further configured to transmit an indication of at least one radio resource control, RRC, state during which a configuration of the second set of beams associated with the plurality of RACH occasions can be used by the UE.

[0085] According to one or more embodiments of this aspect, the network node is further configured to transmit an indication that at least one of the second set of beams associated with a plurality of RACH occasions is spatially contained within one of the first set of beams associated with a plurality of SSBs.

[0086] According to one or more embodiments of this aspect, the network node is further configured to configure the second set of beams associated with a plurality of RACH occasions to correspond to a plurality of beams configured for channel state informationreference signal, CSI-RS, transmission.

[0087] According to one or more embodiments of this aspect, the network node is further configured to receive UE capability information from the UE, where the indication of the first set of beams and the indication of the second set of beams are in response to the UE capability information.

[0088] According to one or more embodiments of this aspect, the indication of the first set of beams and the indication of the second set of beams are included in one of: at least one system information block, SIB; radio resource control, RRC, signaling; or layer 1, LI, message. According to one or more embodiments of this aspect, the PRACH signaling comprises a PRACH preamble of a random access procedure.

[0089] According to one or more embodiments of this aspect, the network node is further configured to transmit an indication that indicates a UE transmission power for transmitting the PRACH signaling is based on at least one characteristic of the second set of beams.

[0090] According to one or more embodiments of this aspect, the network node is further configured to transmit an indication in the first set of beams, where the indication indicates at least one procedure to implement at the UE if the UE lacks the capability to use a machine learning model for beam selection.

[0091] BRIEF DESCRIPTION OF THE DRAWINGS

[0092] A more complete understanding of the present embodiments, and the attendant advantages and features thereof, will be more readily understood by reference to the following detailed description when considered in conjunction with the accompanying drawings wherein:

[0093] FIG. 1 is a diagram of a Set A and Set B of beams within the AI / ML BM use case;

[0094] FIG. 2 is a diagram of CDF of the RSRP difference between the best transmission / reception narrow beam and the narrow beam selected by different methods;

[0095] FIG. 3 is a diagram of a transmission of beamformed SS blocks;

[0096] FIG. 4 is a diagram of a 4-step RACH procedure of 3GPP Rel-15;

[0097] FIG. 5 is a diagram of two steps of an initial access procedure;

[0098] FIG. 6 is a diagram of a 2-step RACH procedure of 3GPP Rel-16;

[0099] FIG. 7 is a schematic diagram of an example network architecture illustrating a communication system according to the principles in the present disclosure;

[0100] FIG. 8 is a block diagram of a network node and a UE communicating over an at least partially wireless connection according to some embodiments of the present disclosure;

[0101] FIG. 9 is a flowchart of an example process in a network node according to some embodiments of the present disclosure;

[0102] FIG. 10 is a flowchart of an example process in a UE according to some embodiments of the present disclosure;

[0103] FIG. 11 is a diagram of an example according to some embodiments of the present disclosure; and FIG. 12 is a flowchart of an example according to some embodiment of the present disclosure.

[0104] DETAILED DESCRIPTION

[0105] Before describing in detail example embodiments, it is noted that the embodiments reside primarily in combinations of apparatus components and processing steps related to random access channel (RACH) communications. Accordingly, components have been represented where appropriate by conventional symbols in the drawings, showing only those specific details that are pertinent to understanding the embodiments so as not to obscure the disclosure with details that will be readily apparent to those of ordinary skill in the art having the benefit of the description herein. Like numbers refer to like elements throughout the description.

[0106] As used herein, relational terms, such as “first” and “second,” “top” and “bottom,” and the like, may be used solely to distinguish one entity or element from another entity or element without necessarily requiring or implying any physical or logical relationship or order between such entities or elements. The terminology used herein is for the purpose of describing particular embodiments only and is not intended to be limiting of the concepts described herein. As used herein, the singular forms “a”, “an” and “the” are intended to include the plural forms as well, unless the context clearly indicates otherwise. It will be further understood that the terms “comprises,” “comprising,” “includes” and / or “including” when used herein, specify the presence of stated features, integers, steps, operations, elements, and / or components, but do not preclude the presence or addition of one or more other features, integers, steps, operations, elements, components, and / or groups thereof.

[0107] In embodiments described herein, the joining term, “in communication with” and the like, may be used to indicate electrical or data communication, which may be accomplished by physical contact, induction, electromagnetic radiation, radio signaling, infrared signaling or optical signaling, for example. One having ordinary skill in the art will appreciate that multiple components may interoperate and modifications and variations are possible of achieving the electrical and data communication.

[0108] In some embodiments described herein, the term “coupled,” “connected,” and the like, may be used herein to indicate a connection, although not necessarily directly, and may include wired and / or wireless connections.

[0109] The term “network node” used herein can be any kind of network node comprised in a radio network which may further comprise any of base station (BS), radio base station, base transceiver station (BTS), base station controller (BSC), radio network controller (RNC), g Node B (gNB), evolved Node B (eNB or eNodeB), Node B, multistandard radio (MSR) radio node such as MSR BS, multi -cell / multicast coordination entity (MCE), integrated access and backhaul (IAB) node, relay node, donor node controlling relay, radio access point (AP), transmission points, transmission nodes, Remote Radio Unit (RRU) Remote Radio Head (RRH), a core network node (e.g., mobile management entity (MME), self-organizing network (SON) node, a coordinating node, positioning node, MDT node, etc.), an external node (e.g., 3rd party node, a node external to the current network), nodes in distributed antenna system (DAS), a spectrum access system (SAS) node, an element management system (EMS), etc. The network node may also comprise test equipment. The term “radio node” used herein may be used to also denote a UE such as a wireless device or a radio network node. Network node may be configured to handle at least some ML operation.

[0110] In some embodiments, the non-limiting terms wireless device (WD) or a user equipment (UE) are used interchangeably. The UE herein can be any type of UE capable of communicating with a network node or another UE over radio signals. The UE may also be a radio communication device, target device, device to device (D2D) UE, machine type UE or UE capable of machine to machine communication (M2M), low-cost and / or low-complexity UE, a sensor equipped with UE, Tablet, mobile terminals, smart phone, laptop embedded equipped (LEE), laptop mounted equipment (LME), USB dongles, Customer Premises Equipment (CPE), an Internet of Things (loT) device, or a Narrowband loT (NB-IOT) device, etc.

[0111] Also, in some embodiments the generic term “radio network node” is used. It can be any kind of a radio network node which may comprise any of base station, radio base station, base transceiver station, base station controller, network controller, RNC, evolved Node B (eNB), Node B, gNB, Multi-cell / multicast Coordination Entity (MCE), IAB node, relay node, access point, radio access point, Remote Radio Unit (RRU) Remote Radio Head (RRH).

[0112] A "model" may refer to an ML-based model, a configuration of an ML-based model, a non-ML-based functionality, or a configuration of a non-ML-based functionality. In one or more embodiments, the model may input one or more parameter(s), value(s), etc. (e.g., RSRP) and output an indication of one or more beams (e.g., best beams)

[0113] The terms “ML-model” and “Al-model” may be used interchangeably herein. An AI / ML model can be defined as functionality or part of the functionality that is deployed / implemented in a first node. This first node can receive a message from a second node indicating that the functionality is not performing correctly. Further, an AI / ML model can be defined as a feature or part of a feature that is implemented / supported in a first node. This first node can indicate the feature version to a second node. If the ML- model is updated, the feature version may be changed by the first node.

[0114] When referring to a "beam" herein, a transmission (Tx) beam may be assumed, i.e., a beam that is used to transmit a signal from the network node detected by the UE. Hence, the term “beam” may be interpreted as a “Tx beam”. If the text refers to a receiver beam, it is referred to as Rx beam or receiver beam.

[0115] Note that although terminology from one particular wireless system, such as, for example, 3GPP LTE and / or New Radio (NR), may be used in this disclosure, this should not be seen as limiting the scope of the disclosure to only the aforementioned system. Other wireless systems, including without limitation Wide Band Code Division Multiple Access (WCDMA), Worldwide Interoperability for Microwave Access (WiMax), Ultra Mobile Broadband (UMB) and Global System for Mobile Communications (GSM), may also benefit from exploiting the ideas covered within this disclosure.

[0116] Note further, that functions described herein as being performed by a UE or a network node may be distributed over a plurality of UEs and / or network nodes. In other words, it is contemplated that the functions of the network node and UE described herein are not limited to performance by a single physical device and, in fact, can be distributed among several physical devices.

[0117] Unless otherwise defined, all terms (including technical and scientific terms) used herein have the same meaning as commonly understood by one of ordinary skill in the art to which this disclosure belongs. It will be further understood that terms used herein should be interpreted as having a meaning that is consistent with their meaning in the context of this specification and the relevant art and will not be interpreted in an idealized or overly formal sense unless expressly so defined herein.

[0118] Some embodiments provide arrangements and methods for RACH communications. Referring again the drawing figures, in which like elements are referred to by like reference numerals, there is shown in FIG. 7 a schematic diagram of a communication system 10, according to an embodiment, such as a 3 GPP -type cellular network that may support standards such as LTE and / or NR (5G), which comprises an access network 12, such as a radio access network, and a core network 14. The access network 12 comprises a plurality of network nodes 16a, 16b, 16c (referred to collectively as network nodes 16), such as NBs, eNBs, gNBs or other types of wireless access points, each defining a corresponding coverage area 18a, 18b, 18c (referred to collectively as coverage areas 18). Each network node 16a, 16b, 16c is connectable to the core network 14 over a wired or wireless connection 20. A first user equipment (UE) 22a located in coverage area 18a is configured to wirelessly connect to, or be paged by, the corresponding network node 16a. A second UE 22b in coverage area 18b is wirelessly connectable to the corresponding network node 16b. While a plurality of UEs 22a, 22b (collectively referred to as UEs 22) are illustrated in this example, the disclosed embodiments are equally applicable to a situation where a sole UE is in the coverage area or where a sole UE 22 is connecting to the corresponding network node 16. Note that although only two UEs 22 and three network nodes 16 are shown for convenience, the communication system may include many more UEs 22 and network nodes 16.

[0119] Also, it is contemplated that a UE 22 can be in simultaneous communication and / or configured to separately communicate with more than one network node 16 and more than one type of network node 16. For example, a UE 22 can have dual connectivity with a network node 16 that supports LTE and the same or a different network node 16 that supports NR. As an example, UE 22 can be in communication with an eNB for LTE / E-UTRAN and a gNB for NR / NG-RAN.

[0120] The communication system 10 comprises intermediate network 30 that may be one of, or a combination of more than one of, a public, private or hosted network. The intermediate network 30, if any, may be a backbone network or the Internet. In some embodiments, the intermediate network 30 may comprise two or more sub-networks (not shown).

[0121] The communication system of FIG. 7 as a whole enables connectivity between one of the connected UEs 22a, 22b and another entity in system 10.

[0122] A network node 16 is configured to include an indication unit 32 which is configured to perform one or more network node 16 functions described herein such as with respect to RACH communications. A UE 22 is configured to include a RACH unit 34 which is configured to perform one or more UE 22 functions as described herein such as with respect to RACH communications.

[0123] Example implementations, in accordance with an embodiment, of the UE 22 and network node 16 discussed in the preceding paragraphs will now be described with reference to FIG. 8. The communication system 10 includes a network node 16 provided in a communication system 10 and including hardware 58 enabling it to communicate with the UE 22. The hardware 58 may include a communication interface 60 for setting up and maintaining a wired or wireless connection with an interface of a different communication device of the communication system 10, as well as a radio interface 62 for setting up and maintaining at least a wireless connection 64 with a UE 22 located in a coverage area 18 served by the network node 16. The radio interface 62 may be formed as or may include, for example, one or more RF transmitters, one or more RF receivers, and / or one or more RF transceivers. The communication interface 60 may be configured to facilitate one or more connections.

[0124] In the embodiment shown, the hardware 58 of the network node 16 further includes processing circuitry 68. The processing circuitry 68 may include a processor 70 and a memory 72. In particular, in addition to or instead of a processor, such as a central processing unit, and memory, the processing circuitry 68 may comprise integrated circuitry for processing and / or control, e.g., one or more processors and / or processor cores and / or FPGAs (Field Programmable Gate Array) and / or ASICs (Application Specific Integrated Circuitry) adapted to execute instructions. The processor 70 may be configured to access (e.g., write to and / or read from) the memory 72, which may comprise any kind of volatile and / or nonvolatile memory, e.g., cache and / or buffer memory and / or RAM (Random Access Memory) and / or ROM (Read-Only Memory) and / or optical memory and / or EPROM (Erasable Programmable Read-Only Memory).

[0125] Thus, the network node 16 further has software 74 stored internally in, for example, memory 72, or stored in external memory (e.g., database, storage array, network storage device, etc.) accessible by the network node 16 via an external connection. The software 74 may be executable by the processing circuitry 68. The processing circuitry 68 may be configured to control any of the methods and / or processes described herein and / or to cause such methods, and / or processes to be performed, e.g., by network node 16. Processor 70 corresponds to one or more processors 70 for performing network node 16 functions described herein. The memory 72 is configured to store data, programmatic software code and / or other information described herein. In some embodiments, the software 74 may include instructions that, when executed by the processor 70 and / or processing circuitry 68, causes the processor 70 and / or processing circuitry 68 to perform the processes described herein with respect to network node 16. For example, processing circuitry 68 of the network node 16 may include indication unit 32 configured to perform one or more network node 16 functions as described herein such as with respect to RACH communications. The communication system 10 further includes the UE 22 already referred to. The UE 22 may have hardware 80 that may include a radio interface 82 configured to set up and maintain a wireless connection 64 with a network node 16 serving a coverage area 18 in which the UE 22 is currently located. The radio interface 82 may be formed as or may include, for example, one or more RF transmitters, one or more RF receivers, and / or one or more RF transceivers.

[0126] The hardware 80 of the UE 22 further includes processing circuitry 84. The processing circuitry 84 may include a processor 86 and memory 88. In particular, in addition to or instead of a processor, such as a central processing unit, and memory, the processing circuitry 84 may comprise integrated circuitry for processing and / or control, e.g., one or more processors and / or processor cores and / or FPGAs (Field Programmable Gate Array) and / or ASICs (Application Specific Integrated Circuitry) adapted to execute instructions. The processor 86 may be configured to access (e.g., write to and / or read from) memory 88, which may comprise any kind of volatile and / or nonvolatile memory, e.g., cache and / or buffer memory and / or RAM (Random Access Memory) and / or ROM (Read-Only Memory) and / or optical memory and / or EPROM (Erasable Programmable Read-Only Memory).

[0127] Thus, the UE 22 may further comprise software 90, which is stored in, for example, memory 88 at the UE 22, or stored in external memory (e.g., database, storage array, network storage device, etc.) accessible by the UE 22. The software 90 may be executable by the processing circuitry 84. The software 90 may include a client application 92. The client application 92 may be operable to provide a service to a human or non-human user via the UE 22. The client application 92 may interact with the user to generate the user data that it provides.

[0128] The processing circuitry 84 may be configured to control any of the methods and / or processes described herein and / or to cause such methods, and / or processes to be performed, e.g., by UE 22. The processor 86 corresponds to one or more processors 86 for performing UE 22 functions described herein. The UE 22 includes memory 88 that is configured to store data, programmatic software code and / or other information described herein. In some embodiments, the software 90 and / or the client application 92 may include instructions that, when executed by the processor 86 and / or processing circuitry 84, causes the processor 86 and / or processing circuitry 84 to perform the processes described herein with respect to UE 22. For example, the processing circuitry 84 of the UE 22 may include a RACH unit 34 configured to perform one or more UE 22 functions as described herein such as with respect to RACH communications.

[0129] In some embodiments, the inner workings of the network node 16 and UE 22 may be as shown in FIG. 8 and independently, the surrounding network topology may be that of FIG. 7.

[0130] The wireless connection 64 between the UE 22 and the network node 16 is in accordance with the teachings of the embodiments described throughout this disclosure. More precisely, the teachings of some of these embodiments may improve the data rate, latency, and / or power consumption and thereby provide benefits such as reduced user waiting time, relaxed restriction on file size, better responsiveness, extended battery lifetime, etc.

[0131] In some embodiments, a measurement procedure may be provided for the purpose of monitoring data rate, latency and other factors on which the one or more embodiments improve.

[0132] In some embodiments, the cellular network also includes the network node 16 with a radio interface 62. In some embodiments, the network node 16 is configured to, and / or the network node’s 16 processing circuitry 68 is configured to perform the functions and / or methods described herein for preparing / initiating / maintaining / supporting / ending a transmission to the UE 22, and / or preparing / terminating / maintaining / supporting / ending in receipt of a transmission from the UE 22.

[0133] In some embodiments, the UE 22 is configured to, and / or comprises a radio interface 82 and / or processing circuitry 84 configured to perform the functions and / or methods described herein for preparing / initiating / maintaining / supporting / ending a transmission to the network node 16, and / or preparing / terminating / maintaining / supporting / ending in receipt of a transmission from the network node 16.

[0134] Although FIGS. 7 and 8 show various “units” such as indication unit 32, and RACH unit 34 as being within a respective processor, it is contemplated that these units may be implemented such that a portion of the unit is stored in a corresponding memory within the processing circuitry. In other words, the units may be implemented in hardware or in a combination of hardware and software within the processing circuitry.

[0135] FIG. 9 is a flowchart of an example process in a network node 16 according to one or more embodiments of the present disclosure. One or more blocks described herein may be performed by one or more elements of network node 16 such as by one or more of processing circuitry 68 (including the indication unit 32), processor 70, radio interface 62 and / or communication interface 60. Network node 16 is configured to indicate (Block SI 00) a first set of beams associated with a plurality of Synchronization Signal Blocks, SSBs, as described herein. Network node 16 is configured to indicate (Block S102) a second set of beams associated with a plurality of random access channel, RACH, occasions, where the first set of beams corresponds to a number of beams that is less than a number of beams of the second set of beams, as described herein. For example, the indication may indicate whether the network node 16 receives RACH transmissions utilizing a larger number of spatial beams than the number of spatial beams used for performing SSB transmissions. Network node 16 is configured to receive (Block S104) physical random access channel, PRACH, signaling on a beam of the second set of beams, where the PRACH signaling is received based on measurement performed on at least one of the first set of beams, as described herein.

[0136] According to one or more embodiments, the network node 16 is further configured to determine, for initial access, the first set of beams associated with a plurality of SSBs and the second set of beams associated with a plurality of RACH occasions.

[0137] According to one or more embodiments, at least one of the beams of the second set of beams associated with a plurality of RACH occasions are configured for selection by the UE 22 using a machine learning model.

[0138] According to one or more embodiments, the network node 16 is further configured to transmit, to the UE 22, an indication of a machine learning model to use for beam selection.

[0139] According to one or more embodiments, at least one of the first set of beams has at least one predefined relationship with respect to at least one of the second set of beams.

[0140] According to one or more embodiments, the at least one predefined relationship is a spatial relationship.

[0141] According to one or more embodiments, at least one of the first set of beams is configured to be measured by the UE 22, where the beam of the second set of beams is selected based on the measurements.

[0142] According to one or more embodiments, the first set of beams are spatially wide beams compared to the beams in the second set of beams.

[0143] According to one or more embodiments, the network node 16 is further configured to transmit an indication of at least one radio resource control, RRC, state during which a configuration of the second set of beams associated with the plurality of RACH occasions can be used by the UE 22.

[0144] According to one or more embodiments, the network node 16 is further configured to transmit an indication that at least one of the second set of beams associated with a plurality of RACH occasions is spatially contained within one of the first set of beams associated with a plurality of SSBs.

[0145] According to one or more embodiments, the network node 16 is further configured to configure the second set of beams associated with a plurality of RACH occasions to correspond to a plurality of beams configured for channel state information-reference signal, CSI-RS, transmission.

[0146] According to one or more embodiments, the network node 16 is further configured to receive UE capability information from the UE 22, where the indication of the first set of beams and the second set of beams is in response to the UE capability information.

[0147] According to one or more embodiments, the indication of the first set of beams and the second set of beams is included in one of at least one system information block, SIB, radio resource control, RRC, signaling, or layer 1, LI, message.

[0148] According to one or more embodiments, the network node 16 is further configured to transfer a model, to the UE 22, for use in selecting the beam of the second set of beams for PRACH signaling.

[0149] According to one or more embodiments, the model is one of a machine learning model and an artificial intelligence model.

[0150] According to one or more embodiments, the PRACH signaling corresponds to or comprises a PRACH preamble of a random access procedure.

[0151] According to one or more embodiments, the network node 16 is further configured to transmit an indication that indicates a UE transmission power for transmitting the PRACH signaling is based on at least one characteristic of the second set of beams.

[0152] According to one or more embodiments, the network node 16 is further configured to transmit an indication in the first set of beams, the indication indicating at least one procedure to implement at the UE 22 if the UE 22 lacks the capability to use a machine learning model for beam selection.

[0153] FIG. 10 is a flowchart of an example process in a UE 22 according to some embodiments of the present disclosure. One or more blocks described herein may be performed by one or more elements of UE 22 such as by one or more of processing circuitry 84 (including the RACH unit 34), processor 86, radio interface 82 and / or communication interface 60. UE 22 is configured to receive (Block SI 06) an indication of a first set of beams associated with a plurality of Synchronization Signal Blocks, SSBs, as described herein. UE 22 is configured to receive (Block SI 08) an indication of a second set of beams associated with a plurality of random access channel, RACH, occasions, where the first set of beams corresponds to a number of beams that is less than a number of beams of the second set of beams, as described herein. UE 22 is configured to perform (Block SI 10) at least one measurement of at least one beam of the first set of beams, as described herein. UE 22 is configured to transmit (Block SI 12) physical random access channel, PRACH, signaling on a beam of the second set of beams based on the at least one measurement, as described herein.

[0154] According to one or more embodiments, the UE 22 is further configured to select, using a machine learning model, the at least one beam of the second set of beams for transmission of the PRACH signaling based on the at least one measurement.

[0155] According to one or more embodiments, the UE 22 is further configured to receive an indication of the machine learning model, and implement the machine learning model based on the received indication.

[0156] According to one or more embodiments, at least one of the first set of beams has at least one predefined relationship with respect to at least one of the second set of beams.

[0157] According to one or more embodiments, the at least one predefined relationship is at least one spatial relationship.

[0158] According to one or more embodiments, the UE 22 is further configured to determine the beam of the second set of beams for use in PRACH signaling based on the at least one measurement of at least one beam of the first set of beams.

[0159] According to one or more embodiments, the first set of beams are spatially wide beams compared to the beams in the second set of beams.

[0160] According to one or more embodiments, the UE 22 is further configured to receive an indication of at least one radio resource control, RRC, state during which a configuration of the second set of beams associated with a plurality of RACH occasions can be used by the UE 22.

[0161] According to one or more embodiments, the UE 22 is further configured to receive an indication that at least one of the second set of beams associated with a plurality of RACH occasions is spatially contained within one of the first set of beams associated with a plurality of SSBs. According to one or more embodiments, the second set of beams associated with a plurality of RACH occasions corresponds to a plurality of beams configured for channel state information-reference signal, CSI-RS, transmission.

[0162] According to one or more embodiments, the UE 22 is further configured to transmit UE capability information, and where the indication of the first set of beams and the second set of beams is in response to the UE capability information.

[0163] According to one or more embodiments, the indication of the first set of beams and the second set of beams is included in one of: at least one system information block, SIB, radio resource control, RRC, signaling; or layer 1, LI, message.

[0164] According to one or more embodiments, the UE 22 is further configured to: receive a model from the network node; and determine the beam of the second set of beams for use in PRACH signaling at least in part by analyzing the at least one measurement with the model.

[0165] According to one or more embodiments, the model is one of a machine learning model and artificial intelligence model. For example, UEs 22 executes the model but which model to select for execution may vary as described herein.

[0166] According to one or more embodiments, the PRACH signaling corresponds to or comprises a PRACH preamble of a random access procedure.

[0167] According to one or more embodiments, the UE 22 is further configured to receive an indication that indicates a UE transmission power for transmitting the PRACH signaling is based on at least one characteristic of the second set of beams.

[0168] According to one or more embodiments, the UE 22 is further configured to receive an indication in the first set of beams, the indication indicating at least one procedure to implement at the UE 22 if the UE 22 lacks a capability to use a machine learning model for beam selection.

[0169] Having described the general process flow of arrangements of the disclosure and having provided examples of hardware and software arrangements for implementing the processes and functions of the disclosure, the sections below provide details and examples of arrangements for RACH communications. One or more network node 16 functions described below may be implemented and / or performed by one or more of processing circuitry 68, processor 70, indication unit 32, communication interface 60, etc. One or more UE 22 functions described below may be implemented and / or performed by one or more of processing circuitry 84, processor 86, RACH unit 34, radio interface 82, etc.

[0170] Some embodiments relate to RACH communications. AI / ML enables the UEs 22 to determine the best narrow beam for data transmission / reception solely based on a limited number of SSB measurements — potentially performed on spatially wide beams. Having such capability allows the network node to communicate to the UE 22 that there does not exist a 1-to-l mapping between spatial beams and uplink RACH transmissions as described herein. For example, a number / quantity of beams of the RACH beams may be less than a number of beams of the SSB beams. In particular, FIGS. 11 and 12 represent an example embodiment and description of an example method, whose steps are described below. The number of downlink SSB beams is reduced, which is feasible based on: i) the uplink-to-downlink power imbalance (the beamforming gain requirement is lower in downlink than in uplink), ii) a UE capability to identify the right narrowband RACH occasion / s where initial access will be performed based on the wide SSB beam measurements.

[0171] With reference to FIG. 12: o Step 1 : Network node 16 indicates information (e.g., in SIB1 and / or in SIB / s different from SIB1 for RRC CONNECTED UEs 22) so that UE 22 attempting to perform initial access determines at least whether the RACH solution described herein is currently being executed by the network node 16, i.e., whether the network node 16 receives RACH transmissions utilizing a larger number of spatial beams than the number of spatial beams used for performing SSB transmissions.

[0172] • For instance, network node 16 may determine to configure narrower spatial beams for RACH reception than those used for performing SSB transmissions. o Step 2: Based on the information received in Step 1, UE 22 determines at least one RACH occasion used for the transmission of at least the PRACH preamble.

[0173] • In some embodiments where the UE 22 determines that the method described herein (i.e., where the number of SSBs is less than the number of RACH beams) is being executed by network node 16, UE 22 executes a model (e.g., Al and / or ML model) whose output will determine one or more RACH occasions where the initial access attempt should be performed. o Step 3 : UE 22 performs the initial access attempt in the at least one RACH occasion with the configuration determined in Step 2. o [Optional] Step: Network node 16 requests for UE 22 to indicate whether it has the capability to execute one or more network indications described in Step 1. o [Optional] Step: UE 22 indicates to network node 16 whether it has the capability to execute one or more of the network indications described in Step 1 and / or whether additional information is required to be provided by network node 16 to execute such indications.

[0174] Further details of the above steps will now be described.

[0175] Step 1:

[0176] In some embodiments, the network node 16 may indicate the following information to be received by the UE 22 prior to performing initial access. Such indication may be performed, e.g., i) within the SIB1 of 5G NR or a signaling with similar functionality in other 3GPP specifications, and / or ii) in SIB(s) different from SIB1 or signaling with similar functionality in other 3 GPP specifications for RRC CONNECTED UEs 22, and / or iii) in a UE 22-specific manner via, e.g., an RRC message, a MAC control element (CE), or a LI message.

[0177] • For instance, in those embodiments where the indication is performed within the SIB 1, the following information may be, e.g., included as a subfield of the RACH- ConfigCommon field.

[0178] In such embodiments, at least one of the information fields may be included: o RRC state of the UE 22: Indicating the RRC states (e.g., RRC CONNECTED, RRC INACTIVE, RRC IDLE) for which the other information fields are applicable. o Indication of whether the network node 16 receives RACH transmissions utilizing a larger number of spatial beams than the number of spatial beams used for performing SSB transmissions (i.e., the method described herein is being executed or performed):

[0179] ■ In some embodiments, the network node 16 will perform such indication via a Boolean information field.

[0180] ■ In some embodiments, the network node 16 will indicate the unique ID associated with each RACH occasion. In the method described herein, the ID will correspond to a specific beam utilized for receiving RACH transmissions.

[0181] The number of unique IDs may be larger than the number of SSB beams if a larger number of beams are used for RACH reception. o In those embodiments where the narrow spatial beams associated with a given RACH occasion are spatially contained within a wider beam used for performing SSB transmission, the network node 16 may indicate such a relationship. For instance, this is the case of the spatially narrow RACH beams #1 and #2 in FIG. 11, which are contained within the spatially wide SSB beam #1. In particular, in FIG. 11, the network node may have 4 antennas that correspond to 4 spatially narrow beams (e.g., RACH beams) and 2 spatially wide beams (e.g., SSB beam where each beam uses 2 antennas) o In some embodiments, the set (or a subset) of the spatial beams used by the network node 16 to receive RACH transmissions may be identical to the beams used for CSI-RS transmissions.

[0182] • In some embodiments, the network node 16 will additionally allocate resources for and indicate the existence of RACH occasions where the reception will be performed utilizing the same spatial beam used for SSB transmission. Allocation of the RACH resources with beams different from those used for SSB transmission: Time and frequency of the RACH occasions the PRACH preamble detection will be performed utilizing beams different from those used for SSB transmission.

[0183] ■ For instance, the network node 16 may indicate for UEs 22 to attempt initial access at a RACH occasion corresponding to the same spatial beam used for SSB transmission, if such RACH occasion exists.

[0184] ■ For instance, the network node 16 may indicate for UE 22 to perform the initial access attempt in a specified number of RACH occasions corresponding to the narrow spatial beams associated with a given RACH occasion when the narrow beams are spatially contained within a wider beam used for performing SSB transmission. The selection may be performed, e.g., randomly. UE model assistance information: Information that the UE 22 can subsequently utilize in Step 2 to identify the model that should be executed to determine the RACH occasion where initial access should be attempted or as an input of a model with the same objective.

[0185] ■ In some embodiments, the network node 16 may indicate to the UE 22 the unique identifier of the model that the latter should execute.

[0186] ■ In some embodiments, the network node 16 may indicate, e.g., a network node product identifier and / or network node antenna array information.

[0187] ■ In some embodiments, the network node 16 may indicate deployment info, such as the antenna physical tilt, antenna physical direction, or antenna physical position.

[0188] ■ In some embodiments, the network node 16 may indicate a beam pattern information, e.g., the angle and direction of a beam. Alternatively, the network node 16 may indicate a unique identifier for the configuration used to transmit all wide and narrow beams. o Indication for UEs 22 without RACH model capability: Indication of the procedure that should be followed by UEs 22 to determine the RACH occasion to perform initial access when UEs 22 are not capable of executing a model that determines the RACH occasion for initial access when there exist RACH occasions associated with narrow beams. o UE model transfer: The network node 16 will transfer model(s) to be subsequently executed by the UE 22 attempting to perform initial access in systems implementing the method described herein.

[0189] ■ Such model(s) will be utilized to, e.g., determine the RACH occasion where initial access should be attempted based on at least the measured SSB transmissions and / or to determine the uplink transmission power when performing the initial access attempt.

[0190] In some embodiments, the mandatory or optional inclusion of one or more of the above information fields as well as the values of such information fields may be indicated by the 3 GPP specification and, consequently, the network information broadcast of such fields may not be performed.

[0191] • For instance, this may occur when the implementation of the AI / ML one-sided beam management model by the UE 22 is a requirement to comply with a certain version of the standard specification. In some embodiments, several replicas of the above information fields, each applicable only to certain UE RRC states and with potentially different values, may be included.

[0192] In some embodiments, the network node 16 will determine whether to include some of the above information fields and / or the values of such information fields based on the UE capability indication provided in the optional Step.

[0193] • For instance, the network node 16 may decide whether a model transfer should be performed if the UE 22 indicates that it has the capability of receiving and executing models to perform initial access in systems implementing the method described herein.

[0194] In some embodiments, the network node 16 may have trained a model that is transferred to the UE 22 (e.g., as part of a SIB transmission). This transfer is considered as options z4 / z5 in 3GPP Technical Reference (TR) 38.843 vO. l.O, where relevant text is described below.

[0195] The following cases further detail the different options for model delivery / transfer to UE 22, training location, and model delivery / transfer format combinations for UE-side models and UE-part of two-sided models:

[0196] The UE 22 can in a related embodiment select to download the model based on its service level requirements. For example, if URLLC is needed, the UE 22 can determine to download the model directly when entering a new cell. In one or more embodiments, UE 22 may use previously measured SSB(s) and / or measured CSI-RS to train the model, i.e., UE-side training location, where the beam(s) used for RACH occasion(s) correspond to the beam(s) used for CSI-RS transmission.

[0197] Step 2:

[0198] Based on the information received in Step 1, the UE 22 decides at least the RACH occasion / s used for the transmission of at least the PRACH preamble.

[0199] • In embodiments where the UE 22 determines that the method described herein is being and / or is configured to be executed and / or performed by the network node 16, the UE 22 will execute a model whose output will determine one or more RACH occasions where the initial access attempt should be performed.

[0200] • In some embodiments where the UE 22 does not have the capability of executing a model to determine the RACH occasion where the UE 22 should perform initial access when there exist RACH occasions associated with narrow beams, the UE 22 will follow the indications provided by the network node 16 to perform such determination and / or the standard specification. In one or more embodiments, UE 22 that does not have the capability to execute a model as described herein may randomly select a beam for initial access. In one or more embodiments, UE 22 may determine whether it has the capability to perform the model based determinations described herein.

[0201] • In some embodiments where the UE 22 determines that the method described herein is not being executed and / or performed, the UE 22 will follow the existing initial access procedure, e.g., as defined in the existing 3GPP specification.

[0202] • In some embodiments, the UE 22 will execute a model whose output will determine the uplink transmission power used for the transmission of the PRACH preamble in the selected RACH occasion. The model will consider at least the received SSB powers and the number / spatial features of the beams used by the network node 16 for RACH reception when performing such uplink transmit power determination.

[0203] Step 3:

[0204] The UE 22 performs the initial access attempt in the at least one RACH occasion with the configuration determined in Step 2.

[0205] [Optional Step]: The network node 16 requests the UE 22 to indicate whether it has the capability to execute one or more network indications described in Step 1.

[0206] • In some embodiments, the network node 16 may perform the request via a network node 16-sent UECapability Enquiry message.

[0207] • For instance, the UE 22 may indicate whether it is capable of receiving via model transfer and / or executing model / s related to initial access functionalities, e.g., determine the RACH occasion where initial access should be attempted based on at least the measured SSB transmissions or to determine the uplink transmission power when performing the initial access attempt.

[0208] • In some embodiments, the request of Step 4 will be part of Step 1.

[0209] [Optional Step]:

[0210] The UE 22 indicates to the network node 16 whether it has the capability to execute one or more network indications described in Step 1 and / or whether additional information is required to be provided by the network node 16 to execute such indications.

[0211] • For instance, the UE 22 may indicate that it is capable and requires the transfer of a model to determine the RACH occasion where initial access should be attempted based on at least the measured SSB transmissions.

[0212] • In some embodiments, the UE 22 may communicate to the network node 16 the UE 22 capability via a UECapability Information message.

[0213] One or more embodiments and / or examples described herein provide one or more of the following advantages. When compared with the state-of-the-art, the method described herein allows an enhanced initial access procedure by:

[0214] 1. reducing the number of SSB transmissions performed by the network node 16 while maintaining uplink coverage — thereby increasing the network node 16’s energy efficiency and initial access latency — or, alternatively,

[0215] 2. enhancing the network node 16’s coverage while maintaining the SSB transmission overhead.

[0216] Some Examples

[0217] Example Al . A network node 16 configured to communicate with a UE 22, the network node configured to: indicate a first set of beams associated with a plurality of Synchronization Signal Blocks, SSBs; indicate a second set of beams associated with a plurality of random access channel, RACH, occasions, the first set of beams corresponding to a number of beams that is less than a number of beams of the second set of beams; and receive physical random access channel, PRACH, signaling on a beam of the second set of beams, the PRACH signaling being received based on measurement performed on at least one of the first set of beams.

[0218] Example A2. The network node 16 of Example Al, wherein at least one of the first set of beams is configured to be measured by the UE 22, the beam of the second set of beams being selected based on the measurements.

[0219] Example A3. The network node 16 of any one of Examples A1-A2, wherein the first set of beams are spatially wide beams compared to the beams in the second set of beams.

[0220] Example A4. The network node 16 of any one of Examples A1-A3, wherein the network node 16 is further configured to receive UE capability information from the UE 22, the indication of the first set of beams and the second set of beams being in response to the UE capability information.

[0221] Example A5. The network node 16 of any one of Examples A1-A4, wherein the indication of the first set of beams and the second set of beams is included in one of: at least one system information block, SIB; radio resource control, RRC, signaling; or layer 1, LI, message.

[0222] Example A6. The network node 16 of any one of Examples A1-A5, wherein the network node 16 is further configured to transfer a model, to the UE 22, for use in selecting the beam of the second set of beams for PRACH signaling.

[0223] Example A7. The network node 16 of Example A6, wherein the model is one of a machine learning model and artificial intelligence model.

[0224] Example A8. The network node 16 of any one of Examples A1-A7, wherein the PRACH signaling corresponds to a PRACH preamble.

[0225] Example Bl. A method implemented by a network node 16 that is configured to communicate with a UE 22, the method comprising: indicating a first set of beams associated with a plurality of Synchronization Signal Blocks, SSBs; indicating a second set of beams associated with a plurality of random access channel, RACH, occasions, the first set of beams corresponding to a number of beams that is less than a number of beams of the second set of beams; and receiving physical random access channel, PRACH, signaling on a beam of the second set of beams, the PRACH signaling being received based on measurement performed on at least one of the first set of beams.

[0226] Example B2. The method of Example Bl, wherein at least one of the first set of beams is configured to be measured by the UE 22, the beam of the second set of beams being selected based on the measurements.

[0227] Example B3. The method of any one of Examples B1-B2, wherein the first set of beams are spatially wide beams compared to the beams in the second set of beams.

[0228] Example B4. The method of any one of Examples B1-B3, further comprising receiving UE capability information from the UE 22, the indication of the first set of beams and the second set of beams being in response to the UE capability information.

[0229] Example B5. The method of any one of Examples B1-B4, wherein the indication of the first set of beams and the second set of beams is included in one of: at least one system information block, SIB; radio resource control, RRC, signaling; or layer 1, LI, message.

[0230] Example B6. The method of any one of Examples B1-B5, further comprising transferring a model, to the UE 22, for use in selecting the beam of the second set of beams for PRACH signaling.

[0231] Example B7. The method of Example B6, wherein the model is one of a machine learning model and artificial intelligence model.

[0232] Example B8. The method of any one of Examples B1-B7, wherein the PRACH signaling corresponds to a PRACH preamble.

[0233] Example Cl . A UE 22 configured to communicate with a network node 16, the UE 22 configured to: receive an indication of a first set of beams associated with a plurality of Synchronization Signal Blocks, SSBs; receive an indication of a second set of beams associated with a plurality of random access channel, RACH, occasions, the first set of beams corresponding to a number of beams that is less than a number of beams of the second set of beams; and perform at least one measurement of at least one beam of the first set of beams; and transmit physical random access channel, PRACH, signaling on a beam of the second set of beams based on the at least one measurement.

[0234] Example C2. The UE 22 of Example Cl, wherein the UE 22 is further configured to determine the beam of the second set of beams for use in PRACH signaling based on the at least one measurement of at least one beam of the first set of beams.

[0235] Example C3. The UE 22 of any one of Examples C1-C2, wherein the first set of beams are spatially wide beams compared to the beams in the second set of beams.

[0236] Example C4. The UE 22 of any one of Examples C1-C3, wherein the UE 22 is further configured to transmit UE capability information; and the indication of the first set of beams and the second set of beams being in response to the UE capability information.

[0237] Example C5. The UE 22 of any one of Examples C1-C4, wherein the indication of the first set of beams and the second set of beams is included in one of at least one system information block, SIB; radio resource control, RRC, signaling; or layer 1, LI, message.

[0238] Example C6. The UE 22 of any one of Examples C1-C5, wherein the UE 22 is further configured to: receive a model from the network node 16; and determine the beam of the second set of beams for use in PRACH signaling at least in part by analyzing the at least one measurement with the model.

[0239] Example C7. The UE 22 of Example C6, wherein the model is one of a machine learning model and artificial intelligence model.

[0240] Example C8. The UE 22 of any one of Examples C1-C7, wherein the PRACH signaling corresponds to a PRACH preamble.

[0241] Example DI . A method implemented by a UE 22 that is configured to communicate with a network node 16, the method comprising: receiving an indication of a first set of beams associated with a plurality of Synchronization Signal Blocks, SSBs; receiving an indication of a second set of beams associated with a plurality of random access channel, RACH, occasions, the first set of beams corresponding to a number of beams that is less than a number of beams of the second set of beams; and performing at least one measurement of at least one beam of the first set of beams; and transmitting physical random access channel, PRACH, signaling on a beam of the second set of beams based on the at least one measurement.

[0242] Example D2. The method of Example DI, further comprising determining the beam of the second set of beams for use in PRACH signaling based on the at least one measurement of at least one beam of the first set of beams.

[0243] Example D3. The method of any one of Examples D1-D2, wherein the first set of beams are spatially wide beams compared to the beams in the second set of beams.

[0244] Example D4. The method of any one of Examples D1-D3, further comprising transmitting UE capability information; and the indication of the first set of beams and the second set of beams being in response to the UE capability information.

[0245] Example D5. The method of any one of Examples D1-D4, wherein the indication of the first set of beams and the second set of beams is included in one of: at least one system information block, SIB; radio resource control, RRC, signaling; or layer 1, LI, message.

[0246] Example D6. The method of any one of Examples D1-D5, further comprising: receiving a model from the network node 16; and determining the beam of the second set of beams for use in PRACH signaling at least in part by analyzing the at least one measurement with the model.

[0247] Example D7. The method of Example D6, wherein the model is one of a machine learning model and artificial intelligence model.

[0248] Embodiment D8. The method of any one of Embodiments D1-D7, wherein the PRACH signaling corresponds to a PRACH preamble.

[0249] As will be appreciated by one of skill in the art, the concepts described herein may be embodied as a method, data processing system, computer program product and / or computer storage media storing an executable computer program. Accordingly, the concepts described herein may take the form of an entirely hardware embodiment, an entirely software embodiment or an embodiment combining software and hardware aspects all generally referred to herein as a “circuit” or “module.” Any process, step, action and / or functionality described herein may be performed by, and / or associated to, a corresponding module, which may be implemented in software and / or firmware and / or hardware. Furthermore, the disclosure may take the form of a computer program product on a tangible computer usable storage medium having computer program code embodied in the medium that can be executed by a computer. Any suitable tangible computer readable medium may be utilized including hard disks, CD-ROMs, electronic storage devices, optical storage devices, or magnetic storage devices.

[0250] Some embodiments are described herein with reference to flowchart illustrations and / or block diagrams of methods, systems and computer program products. It will be understood that each block of the flowchart illustrations and / or block diagrams, and combinations of blocks in the flowchart illustrations and / or block diagrams, can be implemented by computer program instructions. These computer program instructions may be provided to a processor of a general purpose computer (to thereby create a special purpose computer), special purpose computer, or other programmable data processing apparatus to produce a machine, such that the instructions, which execute via the processor of the computer or other programmable data processing apparatus, create means for implementing the functions / acts specified in the flowchart and / or block diagram block or blocks.

[0251] These computer program instructions may also be stored in a computer readable memory or storage medium that can direct a computer or other programmable data processing apparatus to function in a particular manner, such that the instructions stored in the computer readable memory produce an article of manufacture including instruction means which implement the function / act specified in the flowchart and / or block diagram block or blocks.

[0252] The computer program instructions may also be loaded onto a computer or other programmable data processing apparatus to cause a series of operational steps to be performed on the computer or other programmable apparatus to produce a computer implemented process such that the instructions which execute on the computer or other programmable apparatus provide steps for implementing the functions / acts specified in the flowchart and / or block diagram block or blocks.

[0253] It is to be understood that the functions / acts noted in the blocks may occur out of the order noted in the operational illustrations. For example, two blocks shown in succession may in fact be executed substantially concurrently or the blocks may sometimes be executed in the reverse order, depending upon the functionality / acts involved. Although some of the diagrams include arrows on communication paths to show a primary direction of communication, it is to be understood that communication may occur in the opposite direction to the depicted arrows.

[0254] Computer program code for carrying out operations of the concepts described herein may be written in an object oriented programming language such as Python, Java® or C++. However, the computer program code for carrying out operations of the disclosure may also be written in conventional procedural programming languages, such as the "C" programming language. The program code may execute entirely on the user's computer, partly on the user's computer, as a stand-alone software package, partly on the user's computer and partly on a remote computer or entirely on the remote computer. In the latter scenario, the remote computer may be connected to the user's computer through a local area network (LAN) or a wide area network (WAN), or the connection may be made to an external computer (for example, through the Internet using an Internet Service Provider).

[0255] Many different embodiments have been disclosed herein, in connection with the above description and the drawings. It will be understood that it would be unduly repetitious and obfuscating to literally describe and illustrate every combination and subcombination of these embodiments. Accordingly, all embodiments can be combined in any way and / or combination, and the present specification, including the drawings, shall be construed to constitute a complete written description of all combinations and subcombinations of the embodiments described herein, and of the manner and process of making and using them, and shall support claims to any such combination or subcombination.

[0256] Abbreviations that may be used in the preceding description include:

[0257] Abbreviation Explanation

[0258] 3GPP 3rd Generation Partnership Project

[0259] Al Artificial Intelligence

[0260] BS Base station

[0261] BWP Bandwidth part

[0262] CSI Channel state information

[0263] DCI Downlink control information gNB Next generation nodeB

[0264] GNSS Global navigation satellite system

[0265] LOS Line-of-sight

[0266] LTE Long term evolution MIMO Multiple-input multiple-output

[0267] ML Machine Learning

[0268] NLOS Non-line-of-sight

[0269] NR New radio

[0270] NW Network

[0271] PDCP Packet data convergence protocol

[0272] QoS Quality of Service

[0273] RAN Radio access network

[0274] RRC Radio Resource Control

[0275] RRM Radio resource management

[0276] RS Reference signal

[0277] RSRP Reference signal received power

[0278] RSRQ Reference signal received quality

[0279] SCG Secondary cell group

[0280] SI Study item

[0281] SINR Signal to interference and noise ratio

[0282] TAG Timing advance group

[0283] UE User equipment

[0284] It will be appreciated by persons skilled in the art that the embodiments described herein are not limited to what has been particularly shown and described herein above. In addition, unless mention was made above to the contrary, it should be noted that all of the accompanying drawings are not to scale. A variety of modifications and variations are possible in light of the above teachings without departing from the scope of the following claims.

Claims

CLAIMS:

1. A method implemented by a user equipment, UE (22), that is configured to communicate with a network node (16), the method comprising: receiving (SI 06) an indication of a first set of beams associated with a plurality of Synchronization Signal Blocks, SSBs; receiving (SI 08) an indication of a second set of beams associated with a plurality of random access channel, RACH, occasions, the first set of beams corresponding to a number of beams that is less than a number of beams of the second set of beams; performing (SI 10) at least one measurement of at least one beam of the first set of beams; and transmitting (SI 12) physical random access channel, PRACH, signaling on a beam of the second set of beams based on the at least one measurement.

2. The method of Claim 1, further comprising selecting, using a machine learning model, the at least one beam of the second set of beams for transmission of the PRACH signaling based on the at least one measurement.

3. The method of any one of Claims 1-2, further comprising: receiving an indication of the machine learning model; and implementing the machine learning model based on the received indication.

4. The method of any one of Claims 1-3, wherein at least one of the first set of beams has at least one predefined relationship with respect to at least one of the second set of beams.

5. The method of Claim 4, wherein the at least one predefined relationship is at least one spatial relationship.

6. The method of any one of Claims 1-5, further comprising receiving an indication of at least one radio resource control, RRC, state during which a configuration of the second set of beams associated with a plurality of RACH occasions can be used by the UE (22).

7. The method of any one of Claims 1-6, further comprising receiving an indication that at least one of the the second set of beams associated with a plurality of RACH occasions is spatially contained within one of the first set of beams associated with a plurality of SSBs.

8. The method of any one of Claims 1-7, wherein the second set of beams associated with a plurality of RACH occasions corresponds to a plurality of beams configured for channel state information-reference signal, CSI-RS, transmission.

9. The method of any one of Claims 1-8, further comprising transmitting UE capability information, the indication of the first set of beams and the second set of beams being in response to the UE capability information.

10. The method of any one of Claims 1-9, wherein the indication of the first set of beams and the indication of the second set of beams are included in one of: at least one system information block, SIB; radio resource control, RRC, signaling; or layer 1, LI, message.

11. The method of any one of Claims 1-10, wherein the PRACH signaling comprises a PRACH preamble of a random access procedure.

12. The method of Claim 11, further comprising receiving an indication that indicates a UE transmission power for transmitting the PRACH signaling is based on at least one characteristic of the second set of beams.

13. The method of any one of Claims 1-12, further comprising receiving an indication in the first set of beams, the indication indicating at least one procedure to implement at the UE (22) if the UE (22) lacks a capability to use a machine learning model for beam selection.

14. A user equipment, UE (22), configured to communicate with a network node (16), the UE (22) configured to:receive an indication of a first set of beams associated with a plurality of Synchronization Signal Blocks, SSBs; receive an indication of a second set of beams associated with a plurality of random access channel, RACH, occasions, the first set of beams corresponding to a number of beams that is less than a number of beams of the second set of beams; perform at least one measurement of at least one beam of the first set of beams; and transmit physical random access channel, PRACH, signaling on a beam of the second set of beams based on the at least one measurement.

15. The UE (22) of Claim 14, wherein the UE (22) is further configured to select, using a machine learning model, the at least one beam of the second set of beams for transmission of the PRACH signaling based on the at least one measurement.

16. The UE (22) of any one of Claims 14-15, wherein the UE (22) is further configured to: receive an indication of the machine learning model; and implement the machine learning model based on the received indication.

17. The UE (22) of any one of Claims 14-16, wherein at least one of the first set of beams has at least one predefined relationship with respect to at least one of the second set of beams.

18. The UE (22) of Claim 17, wherein the at least one predefined relationship is at least one spatial relationship.

19. The UE (22) of any one of Claims 14-18, wherein the UE (22) is further configured to receive an indication of at least one radio resource control, RRC, state during which a configuration of the second set of beams associated with a plurality of RACH occasions can be used by the UE (22).

20. The UE (22) of any one of Claims 14-19, wherein the UE (22) is further configured to receive an indication that at least one of the second set of beams associatedwith a plurality of RACH occasions is spatially contained within one of the first set of beams associated with a plurality of SSBs.

21. The UE (22) of any one of Claims 14-20, wherein the second set of beams associated with a plurality of RACH occasions corresponds to a plurality of beams configured for channel state information-reference signal, CSI-RS, transmission.

22. The UE (22) of any one of Claims 14-21, wherein the UE (22) is further configured to transmit UE capability information, the indication of the first set of beams and the second set of beams being in response to the UE capability information.

23. The UE (22) of any one of Claims 14-22, wherein the indication of the first set of beams and the indication of the second set of beams are included in one of: at least one system information block, SIB; radio resource control, RRC, signaling; or layer 1, LI, message.

24. The UE (22) of any one of Claims 14-23, wherein the PRACH signaling comprises a PRACH preamble of a random access procedure.

25. The UE (22) of Claim 24, wherein the UE (22) is further configured to receive an indication that indicates a UE transmission power for transmitting the PRACH signaling is based on at least one characteristic of the second set of beams.

26. The UE (22) of any one of Claims 14-25, wherein the UE (22) is further configured to receive an indication in the first set of beams, the indication indicating at least one procedure to implement at the UE (22) if the UE (22) lacks a capability to use a machine learning model for beam selection.

27. A method implemented by a network node (16) that is configured to communicate with a user equipment, UE (22), the method comprising: indicating (SI 00) a first set of beams associated with a plurality of Synchronization Signal Blocks, SSBs;indicating (SI 02) a second set of beams associated with a plurality of random access channel, RACH, occasions, the first set of beams corresponding to a number of beams that is less than a number of beams of the second set of beams; and receiving (SI 04) physical random access channel, PRACH, signaling on a beam of the second set of beams, the PRACH signaling being received based on measurement performed on at least one of the first set of beams.

28. The method of Claim 27, further comprising determining, for initial access, the first set of beams associated with a plurality of SSBs and the second set of beams associated with a plurality of RACH occasions.

29. The method of any one of Claims 27-28, wherein at least one of the beams of the second set of beams associated with a plurality of RACH occasions are configured for selection by the UE (22) using a machine learning model.

30. The method of any one of Claims 27-29, further comprising transmitting, to the UE (22), an indication of a machine learning model to use for beam selection.

31. The method of any one of Claims 27-30, wherein at least one of the first set of beams has at least one predefined relationship with respect to at least one of the second set of beams.

32. The method of Claim 31, wherein the at least one predefined relationship is a spatial relationship.

33. The method of any one of Claims 27-32, further comprising transmitting an indication of at least one radio resource control, RRC, state during which a configuration of the second set of beams associated with the plurality of RACH occasions can be used by the UE (22).

34. The method of any one of Claims 27-33, further comprising transmitting an indication that at least one of the second set of beams associated with a plurality of RACH occasions is spatially contained within one of the first set of beams associated with a plurality of SSBs.

35. The method of any one of Claims 27-34, further comprising configuring the second set of beams associated with a plurality of RACH occasions to correspond to a plurality of beams configured for channel state information-reference signal, CSI-RS, transmission.

36. The method of any one of Claims 27-35, further comprising receiving UE capability information from the UE (22), the indication of the first set of beams and the indication of the second set of beams being in response to the UE capability information.

37. The method of any one of Claims 27-36, wherein the indication of the first set of beams and the indication of the second set of beams are included in one of: at least one system information block, SIB; radio resource control, RRC, signaling; or layer 1, LI, message.

38. The method of any one of Claims 27-37, wherein the PRACH signaling comprises a PRACH preamble of a random access procedure.

39. The method of Claim 38, further comprising transmitting an indication that indicates a UE transmission power for transmitting the PRACH signaling is based on at least one characteristic of the second set of beams.

40. The method of any one of Claims 27-39, further comprising transmitting an indication in the first set of beams, the indication indicating at least one procedure to implement at the UE (22) if the UE (22) lacks the capability to use a machine learning model for beam selection.

41. A network node (16) that is configured to communicate with a user equipment, UE (22), the network node (16) configured to: indicate a first set of beams associated with a plurality of Synchronization Signal Blocks, SSBs;indicate a second set of beams associated with a plurality of random access channel, RACH, occasions, the first set of beams corresponding to a number of beams that is less than a number of beams of the second set of beams; and receive physical random access channel, PRACH, signaling on a beam of the second set of beams, the PRACH signaling being received based on measurement performed on at least one of the first set of beams.

42. The network node (16) of Claim 41, wherein the network node (16) is further configured to determine, for initial access, the first set of beams associated with a plurality of SSBs and the second set of beams associated with a plurality of RACH occasions.

43. The network node (16) of any one of Claims 41-42, wherein at least one of the beams of the second set of beams associated with a plurality of RACH occasions are configured for selection by the UE (22) using a machine learning model.

44. The network node (16) of any one of Claims 41-43, wherein the network node (16) is further configured to transmit, to the UE (22), an indication of a machine learning model to use for beam selection.

45. The network node (16) of any one of Claims 41-44, wherein at least one of the first set of beams has at least one predefined relationship with respect to at least one of the second set of beams.

46. The network node (16) of Claim 45, wherein the at least one predefined relationship is a spatial relationship.

47. The network node (16) of any one of Claims 41-46, wherein the network node (16) is further configured to transmit an indication of at least one radio resource control, RRC, state during which a configuration of the second set of beams associated with the plurality of RACH occasions can be used by the UE (22).

48. The network node (16) of any one of Claims 41-47, wherein the network node (16) is further configured to transmit an indication that at least one of the second setof beams associated with a plurality of RACH occasions is spatially contained within one of the first set of beams associated with a plurality of SSBs.

49. The network node (16) of any one of Claims 41-48, wherein the network node (16) is further configured to configure the second set of beams associated with a plurality of RACH occasions to correspond to a plurality of beams configured for channel state information-reference signal, CSI-RS, transmission.

50. The network node (16) of any one of Claims 41-49, wherein the network node (16) is further configured to receive UE capability information from the UE (22), the indication of the first set of beams and the indication of the second set of beams being in response to the UE capability information.

51. The network node (16) of any one of Claims 41-50, wherein the indication of the first set of beams and the indication of the second set of beams are included in one of: at least one system information block, SIB; radio resource control, RRC, signaling; or layer 1, LI, message.

52. The network node (16) of any one of Claims 41-51, wherein the PRACH signaling comprises a PRACH preamble of a random access procedure.

53. The network node (16) of Claim 52, wherein the network node (16) is further configured to transmit an indication that indicates a UE transmission power for transmitting the PRACH signaling is based on at least one characteristic of the second set of beams.

54. The network node (16) of any one of Claims 41-53, wherein the network node (16) is further configured to transmit an indication in the first set of beams, the indication indicating at least one procedure to implement at the UE (22) if the UE (22) lacks the capability to use a machine learning model for beam selection.

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